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Title: West Flank Coso, CA FORGE 83-11 image and mud log data

CBIL and STAR image logs as pre-processed DLIS files, and mud log of well 83-11
Authors:
Publication Date:
Report Number(s):
746
DOE Contract Number:
EE0007156
Product Type:
Dataset
Research Org(s):
DOE Geothermal Data Repository; Sandia National Laboratories
Collaborations:
Sandia National Laboratories
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Program (EE-2C)
Subject:
15 Geothermal Energy; geothermal; FORGE; EGS; West Flank Coso; well data; Coso; mud log; image log
OSTI Identifier:
1287549
  1. The Geothermal Data Repository (GDR) is the submission point for all data collected from researchers funded by the U.S. Department of Energy's Geothermal Technologies Office (DOE GTO). The DOE GTO is providing access to its geothermal project information through the GDR. The GDR is powered by OpenEI, an energy information portal sponsored by the U.S. Department of Energy and developed by the National Renewable Energy Laboratory (NREL).
No associated Collections found.
  1. This submission of Utilization Analysis data to the Geothermal Data Repository (GDR) node of the National Geothermal Data System (NGDS) is in support of Phase 1 Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (project DE-EE0006726). The submission includes data pertinent to themore » methods and results of an analysis of the Surface Levelized Cost of Heat (SLCOH) for US Census Bureau ‘Places’ within the study area. This was calculated using a modification of a program called GEOPHIRES, available at http://koenraadbeckers.net/geophires/index.php. The MATLAB modules used in conjunction with GEOPHIRES, the MATLAB data input file, the GEOPHIRES output data file, and an explanation of the software components have been provided. Results of the SLCOH analysis appear on 4 .png image files as mapped ‘risk’ of heat utilization. For each of the 4 image (.png) files, there is an accompanying georeferenced TIF (.tif) file by the same name. In addition to calculating SLCOH, this Task 4 also identified many sites that may be prospects for use of a geothermal district heating system, based on their size and industry, rather than on the SLCOH. An industry sorted listing of the sites (.xlsx) and a map of these sites plotted as a layer onto different iterations of maps combining the three geological risk factors (Thermal Quality, Natural Reservoir Quality, and Risk of Seismicity) has been provided. In addition to the 6 image (.png) files of the maps in this series, a shape (.shp) file and 7 associated files are included as well. Finally, supporting files (.pdf) describing the utilization analysis methodology and summarizing the anticipated permitting for a deep district heating system are supplied. « less
  2. This submission of Utilization Analysis data to the Geothermal Data Repository (GDR) node of the National Geothermal Data System (NGDS) is in support of Phase 1 Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (project DE-EE0006726). The submission includes data pertinent to themore » methods and results of an analysis of the Surface Levelized Cost of Heat (SLCOH) for US Census Bureau ‘Places’ within the study area. This was calculated using a modification of a program called GEOPHIRES, available at http://koenraadbeckers.net/geophires/index.php. The MATLAB modules used in conjunction with GEOPHIRES, the MATLAB data input file, the GEOPHIRES output data file, and an explanation of the software components have been provided. Results of the SLCOH analysis appear on 4 .png image files as mapped ‘risk’ of heat utilization. For each of the 4 image (.png) files, there is an accompanying georeferenced TIF (.tif) file by the same name. In addition to calculating SLCOH, this Task 4 also identified many sites that may be prospects for use of a geothermal district heating system, based on their size and industry, rather than on the SLCOH. An industry sorted listing of the sites (.xlsx) and a map of these sites plotted as a layer onto different iterations of maps combining the three geological risk factors (Thermal Quality, Natural Reservoir Quality, and Risk of Seismicity) has been provided. In addition to the 6 image (.png) files of the maps in this series, a shape (.shp) file and 7 associated files are included as well. Finally, supporting files (.pdf) describing the utilization analysis methodology and summarizing the anticipated permitting for a deep district heating system are supplied. « less
  3. Hurricane Maria made landfall as a strong Category 4 storm in southeast Puerto Rico on September 20th, 2018. The powerful storm traversed the island in a northwesterly direction causing widespread destruction. This study focused on a rapid assessment of Hurricane Marias impact to Puerto Ricosmore » forests. Calibrated and corrected Landsat 8 image composites for the entire island were generated using Google Earth Engine for a comparable pre-Maria and post-Maria time period that accounted for phenology. Spectral mixture analysis (SMA) using image-derived end members was carried out on both composites to calculate the change in the non-photosynthetic vegetation (Delta-NPV) spectral response, a metric that quantifies the increased fraction of exposed wood and surface litter associated with tree mortality and crown damage from the storm. Hurricane simulations were also conducted using the Weather Research and Forecasting (WRF) regional climate model to estimate wind speeds associated with forest disturbance. Dramatic changes in forest structure across the entire island were evident from pre- and post-Maria composited Landsat 8 images. A Delta-NPV map for only the forested pixels illustrated significant spatial variability in disturbance, with patterns that associated with factors such as slope, aspect and elevation. An initial order-of-magnitude impact estimate based on previous work indicated that Hurricane Maria may have caused mortality and severe damage to 23-31 million trees. Additional field work and image analyses are required to further detail the impact of Hurricane Maria to Puerto Rico forests. A minor update to this dataset was posted on April 20, 2018. The previous version is being retired. If you need access to the prior version of the data, email ngee-tropics-archive@lbl.gov. « less
  4. This submission has two shapefiles and a tiff image. The weights of evidence analysis was applied to data representing heat of the earth and fracture permeability using training sites around the Southwest; this is shown in the tiff image. A shapefile of surface temperature anomaliesmore » was derived from the statistical analysis of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) thermal infrared data which had been converted to surface temperatures; these anomalies have not been field checked. The second shapefile shows outcrop mineralogy which originally mapped by the New Mexico Bureau of Geology and Mineral Resources, and supplemented with mineralogic information related to rock fracability risk for EGS. Further metadata can be found within each file. « less
  5. The SP2 provides information on the amounts of rBC (refractory black carbon) and of other, non-refractory substances associated with individual rBC containing particles by simultaneously measuring the scattering and incandescence signals of such particles that are directed through the cavity of a 1064 nm Nd:YAGmore » laser. (refractory Black Carbon) rBC mixing ratio (ng/Kg) and number size distribution time series collected during the DOE-ARM sponsored ACME-V field campaign held from June 1 to September 15, 2015 rBC mixing ratio is reported at STP conditions Time resolution: 10 sec Uncertainty: ~ 30% SP2 Unit: 25 Location: Deadhorse, AK Location: N 70-degree 11' 41'' - W 148-degress. 27' 55'' SP2_dateTime: UTC rBC concentration is in units of ng/Kg - dry air. Mass Equivalent Diameters [MED] used for size distribution (SP2_min; SP2_geo; and SP2_max) are in units of micrometers dN/dlogDp counts for a given size bin (SP2_geo) listed as 'SP2_cnts_0 - SP2_cnts_199' and are in units of #/cc. Column naming convention: 'SP2_cnts_X' are the number of particles in bin number _X. , where _X is the row number within the 'SP2_geo' size bin column that contains the mass equivalent diameter (e.g., SP2_cnts_0 = 0.01 microns; SP2_cnts_10 = 0.060 microns, etc.). The dN/dlogDp data is time-resolved where a given row is associated with the timestamp for that row. Note that the rBC column length is one field shorter than the SP2_datetime column. Last time field is not relevant to the rBC time series (see comment below on length of SP2_datetime column) Lengths for SP2_max; SP2_min; SP2_geo are one field longer then the number of SP2_cnts_XX columns . This is to provide bounds for image plots (if desired). Length for SP2_datetime is one field longer than that length of the SP2_cnts_XX columns This is to provide bounds for image plots (if desired) SP2 Calibration: Fullerene soot with corrrection applied for particle density as a function of particle size. No correction for OC content in Fullerene (recent study on SP2 sensitivity to differing black carbon types reports that non-refractory material content for fullerene soot is about 20%). « less